Variational Inference papers, 2023–2026

Key findings

• Variational Inference fell from 106 papers in 2023 to 91 in 2026, so interest is cooling.
• NeurIPS publishes the most Variational Inference work: 124 papers from 2023 to 2026, 35% of the four-venue total.
• The fastest-growing overlap is with Sampling Methods: papers tagged with both rose from 1 in 2023 to 6 in 2026.
• Among the 5 topics under Probabilistic and Bayesian, it ranks #5 by 2026 paper count; the fastest grower in the group, Gaussian Processes, is up 2.2x versus 0.9x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026A Reproducible Evaluation Protocol for Quantum Non-Linearity in Variational Quantum Models
• ICML 2026Beyond Independence: Learning Correlated Views for Variational Incomplete Multi-View Clustering
• ICLR 2026Optimizing Data Augmentation through Bayesian Model Selection
• CVPR 2026BrepVGAE Variational Graph Autoencoder with Unified Latent Representation for B-rep
• NeurIPS 2025Covariate-moderated Empirical Bayes Matrix Factorization
• ICML 2025A Variational Information Theoretic Approach to Out-of-Distribution Detection
• ICLR 2025Bridging the Gap between Variational Inference and Stochastic Gradient MCMC in Function Space
• CVPR 2025Dora: Sampling and Benchmarking for 3D Shape Variational Auto-Encoders
• NeurIPS 2024Training Binary Neural Networks via Gaussian Variational Inference and Low-Rank Semidefinite Programming
• ICML 2024Amortized Variational Deep Kernel Learning
• ICLR 2024Causal Inference with Conditional Front-Door Adjustment and Identifiable Variational Autoencoder
• CVPR 2024WorDepth: Variational Language Prior for Monocular Depth Estimation
• NeurIPS 2023[Re] Variational Neural Cellular Automata
• ICML 2023Coupled Variational Autoencoder
• ICLR 2023A VAE for Transformers with Nonparametric Variational Information Bottleneck
• CVPR 2023Confidence-Aware Personalized Federated Learning via Variational Expectation Maximization
• NeurIPS 2026Adaptive Delayed-Update Cyclic Algorithm for Variational Inequalities
• ICML 2026Dual-stage Contrastive Learning-enhanced Multi-view Variational Clustering
• ICLR 2026Pareto Variational Autoencoder
• CVPR 2026Variational Graph-based Normal Integration

All Variational Inference papers

110 papers, page 2 of 3

51. ICLR 2025When do GFlowNets learn the right distribution?
52. ICLR 2024$t^3$-Variational Autoencoder: Learning Heavy-tailed Data with Student's t and Power Divergence
53. ICLR 2024A Variational Framework for Estimating Continuous Treatment Effects with Measurement Error
54. ICLR 2024A Variational Perspective on Solving Inverse Problems with Diffusion Models
55. ICLR 2024Beyond Vanilla Variational Autoencoders: Detecting Posterior Collapse in Conditional and Hierarchical Variational Autoencoders
56. ICLR 2024Causal Inference with Conditional Front-Door Adjustment and Identifiable Variational Autoencoder
57. ICLR 2024Communication-Efficient Gradient Descent-Accent Methods for Distributed Variational Inequalities: Unified Analysis and Local Updates
58. ICLR 2024Conditional Variational Diffusion Models
59. ICLR 2024Decoupled Marked Temporal Point Process using Neural Ordinary Differential Equations
60. ICLR 2024DiffEnc: Variational Diffusion with a Learned Encoder
61. ICLR 2024Disentangling Time Series Representations via Contrastive Independence-of-Support on l-Variational Inference
62. ICLR 2024Fast Ensembling with Diffusion Schrödinger Bridge
63. ICLR 2024Fiber Monte Carlo
64. ICLR 2024Forward $\chi^2$ Divergence Based Variational Importance Sampling
65. ICLR 2024Input-gradient space particle inference for neural network ensembles
66. ICLR 2024Kernelised Normalising Flows
67. ICLR 2024Lewis's Signaling Game as beta-VAE For Natural Word Lengths and Segments
68. ICLR 2024MINDE: Mutual Information Neural Diffusion Estimation
69. ICLR 2024R-EDL: Relaxing Nonessential Settings of Evidential Deep Learning
70. ICLR 2024Rethinking the symmetry-preserving circuits for constrained variational quantum algorithms
71. ICLR 2024Stochastic Gradient Descent for Gaussian Processes Done Right
72. ICLR 2024Training Bayesian Neural Networks with Sparse Subspace Variational Inference
73. ICLR 2024Transport meets Variational Inference: Controlled Monte Carlo Diffusions
74. ICLR 2024Uncertainty Quantification via Stable Distribution Propagation
75. ICLR 2024Variational Bayesian Last Layers
76. ICLR 2024Variational Inference for SDEs Driven by Fractional Noise
77. ICLR 2023A Unified Approach to Reinforcement Learning, Quantal Response Equilibria, and Two-Player Zero-Sum Games
78. ICLR 2023A VAE for Transformers with Nonparametric Variational Information Bottleneck
79. ICLR 2023Approximate Bayesian Inference with Stein Functional Variational Gradient Descent
80. ICLR 2023Benchmarking Constraint Inference in Inverse Reinforcement Learning
81. ICLR 2023Calibrating Transformers via Sparse Gaussian Processes
82. ICLR 2023Classically Approximating Variational Quantum Machine Learning with Random Fourier Features
83. ICLR 2023DAVA: Disentangling Adversarial Variational Autoencoder
84. ICLR 2023Deep Variational Implicit Processes
85. ICLR 2023Denoising Diffusion Samplers
86. ICLR 2023Domain-Indexing Variational Bayes: Interpretable Domain Index for Domain Adaptation
87. ICLR 2023Explicitly Minimizing the Blur Error of Variational Autoencoders
88. ICLR 2023Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach
89. ICLR 2023Function-space regularized Rényi divergences
90. ICLR 2023GFlowNets and variational inference
91. ICLR 2023Gromov-Wasserstein Autoencoders
92. ICLR 2023Interpretations of Domain Adaptations via Layer Variational Analysis
93. ICLR 2023Learning Continuous Normalizing Flows For Faster Convergence To Target Distribution via Ascent Regularizations
94. ICLR 2023Learning Group Importance using the Differentiable Hypergeometric Distribution
95. ICLR 2023Learning on Large-scale Text-attributed Graphs via Variational Inference
96. ICLR 2023Learning with Logical Constraints but without Shortcut Satisfaction
97. ICLR 2023Optimal Activation Functions for the Random Features Regression Model
98. ICLR 2023Particle-based Variational Inference with Preconditioned Functional Gradient Flow
99. ICLR 2023Predicting Cellular Responses with Variational Causal Inference and Refined Relational Information
100. ICLR 2023Real-time variational method for learning neural trajectory and its dynamics

FAQ

How many Variational Inference papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

359 in total: 106 in 2023, 76 in 2024, 86 in 2025, 91 in 2026.

How many Variational Inference papers are at NeurIPS 2026?

NeurIPS 2026 has 30 Variational Inference papers, versus 28 the year before.

How many Variational Inference papers are at ICLR 2026?

ICLR 2026 has 23 Variational Inference papers, versus 28 the year before.

How many Variational Inference papers are at ICML 2026?

ICML 2026 has 35 Variational Inference papers, versus 28 the year before.

How many Variational Inference papers are at CVPR 2026?

CVPR 2026 has 3 Variational Inference papers, versus 2 the year before.

Which conference publishes the most Variational Inference papers?

NeurIPS, with 124 papers from 2023 to 2026.